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Mathematical analysis of multiple spike time series synchronized in phase with collective theta wave using neural cell model
Electronics and Communications in Japan ( IF 0.3 ) Pub Date : 2020-12-24 , DOI: 10.1002/ecj.12294
Hiroki Noyama 1 , Yuto Yoshikai 1 , Kiyoshi Kotani 1 , Yasuhiko Jimbo 2
Affiliation  

Information processing in the brain is performed by the interactions of numerous number of neurons. However, much remains unknown about complex behaviors of a network composed of numerous number of neurons. Especially, in what case cross frequency coupling emerges and how it alters timings of individual firing are open questions. Therefore, in order to quantitatively evaluate the dynamics of the nervous group, we reproduced phenomena such as cross frequency coupling observed in the brain on a mathematical model and analyzed. The analyses of Fokker‐Planck equation provide the region of gamma/theta oscillations as well as their cross‐frequency couplings. In addition, we demonstrated that the populational oscillation synchronizes sequences of spike trains, which is supposed to be a possible mechanism of memory coding in hippocampus by theta‐gamma neural code.

中文翻译:

神经细胞模型对与集体θ波同相同步的多个峰值时间序列的数学分析

大脑中的信息处理是通过大量神经元的相互作用来执行的。但是,关于由众多神经元组成的网络的复杂行为,仍然知之甚少。特别是,在什么情况下会出现交叉频率耦合以及它如何改变单个触发的时间,这是悬而未决的问题。因此,为了定量评估神经群的动态,我们在数学模型上重现了诸如在大脑中观察到的交叉频率耦合现象,并进行了分析。Fokker-Planck方程的分析提供了伽玛/θ振荡的区域以及它们的跨频耦合。此外,我们证明了总体振动使尖峰序列的序列同步,
更新日期:2020-12-24
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